{"id":"W2031056773","doi":"10.1007/s10994-012-5316-5","title":"Quantum speed-up for unsupervised learning","year":2012,"lang":"en","type":"article","venue":"Machine Learning","topic":"Quantum Computing Algorithms and Architecture","field":"Computer Science","cited_by":213,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Computer science; Cluster analysis; Unsupervised learning; Initialization; Graph; Speedup; Quantum; Quantum machine learning; Theoretical computer science; Quantization (signal processing); Algorithm; Artificial intelligence; Quantum algorithm","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009488318,0.000247967,0.0002599452,0.0001492463,0.0006705517,0.0001891233,0.0006435587,0.00007940943,0.00002917149],"category_scores_gemma":[0.0003170111,0.0002187761,0.0001597397,0.0003487815,0.0000295844,0.0003140524,0.000341859,0.0006737438,0.00006895092],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002735225,"about_ca_system_score_gemma":0.00002725611,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005126415,"about_ca_topic_score_gemma":0.000001567702,"domain_scores_codex":[0.9980759,0.0002085863,0.0002579137,0.0003953631,0.000266408,0.0007958121],"domain_scores_gemma":[0.9989432,0.0003569515,0.0001319527,0.0003052455,0.000058558,0.0002040536],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004948697,0.0002083024,0.09246003,0.000176697,0.0001122395,0.00001345633,0.01390469,0.2212991,0.005262007,0.04449949,0.0009265791,0.6210879],"study_design_scores_gemma":[0.000495929,0.0001718123,0.002745099,0.00002515938,0.000007965884,0.00003455772,0.00004735575,0.9136071,0.0002729472,0.0004617853,0.08184008,0.0002901754],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2756375,0.0009996658,0.7194963,0.0008646094,0.001261375,0.0002095713,0.00000140384,0.0008387761,0.0006908047],"genre_scores_gemma":[0.962332,0.000008294269,0.03527698,0.0002331207,0.0006591195,0.000007449066,0.00001610413,0.00004019715,0.001426768],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.692308,"threshold_uncertainty_score":0.892143,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01650694066603725,"score_gpt":0.2562202338761764,"score_spread":0.2397132932101392,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}